{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day17 进阶构图元素——色彩篇（上）\n",
    "\n",
    "　　色彩是我们创作数据可视化作品非常非常重要的视觉元素，是查看图表的人最先可以从我们的数据可视化作品中感知到的元素，在`matplotlib`中运用色彩有很多知识点，我们将分上下篇对其中常用的重要知识进行介绍。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:36.627569Z",
     "iopub.status.busy": "2020-11-03T10:51:36.627569Z",
     "iopub.status.idle": "2020-11-03T10:51:36.843982Z",
     "shell.execute_reply": "2020-11-03T10:51:36.843982Z",
     "shell.execute_reply.started": "2020-11-03T10:51:36.627569Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matplotlib版本： 3.3.2\n"
     ]
    }
   ],
   "source": [
    "import matplotlib;print('matplotlib版本：', matplotlib.__version__)\n",
    "import matplotlib.pyplot as plt # 从matplotlib中导入我们最经常使用的pyplot子模\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 设定默认字体为SimHei以解决中文显示乱码问题\n",
    "plt.rcParams['axes.unicode_minus'] = False # 解决图像负号'-'不正常显示的问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　在前面日程所学的`matplotlib`常用API中，很多都涉及到颜色的设置，在`matplotlib`中运用色彩主要有设置**单一色彩**与设置**连续色彩映射**两种，作为**（上篇）**我们先来学习单一色彩的设置。\n",
    "\n",
    "　　在`matplotlib`中设置**单一色彩**主要有以下几种格式："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 色彩名称\n",
    "\n",
    "　　第一种定义**单一色彩**的方法直接传入一些经典的具有名称的字符串，常用的色彩见下图：\n",
    "  \n",
    "<center>\n",
    "    <img src=\"imgs/colors.png\"></img>\n",
    "</center>\n",
    "\n",
    "　　使用方式如下面的例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:36.845976Z",
     "iopub.status.busy": "2020-11-03T10:51:36.845976Z",
     "iopub.status.idle": "2020-11-03T10:51:36.978636Z",
     "shell.execute_reply": "2020-11-03T10:51:36.977657Z",
     "shell.execute_reply.started": "2020-11-03T10:51:36.845976Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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sMoAaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.bar(0, 1, color='b')\n",
    "ax.bar(1, 2, color='tab:olive')\n",
    "ax.bar(2, 3, color='steelblue');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 RGB与RGBA元组\n",
    "\n",
    "　　`RGB`以三元组的形式来表示红、绿、蓝三个通道上的色彩，每个位置上的元素取值在0到255之间，但在`matplotlib`中要求每个位置上的值需要标准化到0-1之间，因此我们在传统`RGB`取值的基础上每个元素除以255即可，就像下面的例子一样："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:36.979613Z",
     "iopub.status.busy": "2020-11-03T10:51:36.979613Z",
     "iopub.status.idle": "2020-11-03T10:51:37.072362Z",
     "shell.execute_reply": "2020-11-03T10:51:37.072362Z",
     "shell.execute_reply.started": "2020-11-03T10:51:36.979613Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.bar(0, 1, color=(100 / 255, 140 / 255, 255 / 255));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　而`RGBA`则在三通道的基础上添加了透明度alpha，使之形成四元组，取值在0-1之间："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:37.073358Z",
     "iopub.status.busy": "2020-11-03T10:51:37.073358Z",
     "iopub.status.idle": "2020-11-03T10:51:37.161122Z",
     "shell.execute_reply": "2020-11-03T10:51:37.161122Z",
     "shell.execute_reply.started": "2020-11-03T10:51:37.073358Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.bar(0, 1, color=(100 / 255, 140 / 255, 255 / 255))\n",
    "ax.bar(1, 1, color=(100 / 255, 140 / 255, 255 / 255, 0.4)); # 施加40%透明度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 十六进制色彩字符串\n",
    "\n",
    "　　除了上述的两种方式外，`matplotlib`还提供了十六进制字符串输入的色彩，这一点我们在前面已经用到很多次了，且支持末尾添加两位数字设置透明度："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:37.162117Z",
     "iopub.status.busy": "2020-11-03T10:51:37.162117Z",
     "iopub.status.idle": "2020-11-03T10:51:37.246889Z",
     "shell.execute_reply": "2020-11-03T10:51:37.246889Z",
     "shell.execute_reply.started": "2020-11-03T10:51:37.162117Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.bar(0, 1, color='#648cff')\n",
    "ax.bar(1, 1, color='#648cff40'); # 施加40%透明度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 课后测验：\n",
    "\n",
    "　　接下来的时间交给你们，因为作为上篇，内容很简单，因此我们在题目中结合色彩的同时增加一些其他方面的难度，我们需要用到一个新的API，这里先简单介绍一下其基础用法。\n",
    "\n",
    "　　我们使用到的新API为`fill_between(x, y1, y2)`，用于填充x相同，y分别为y1和y2的两条折线之间的区域，譬如下面这个简单的例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:37.248882Z",
     "iopub.status.busy": "2020-11-03T10:51:37.247884Z",
     "iopub.status.idle": "2020-11-03T10:51:37.338640Z",
     "shell.execute_reply": "2020-11-03T10:51:37.338640Z",
     "shell.execute_reply.started": "2020-11-03T10:51:37.248882Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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HgwcPlC0wXdexadMmvP/++1ZHodewxOitHj58CJ/Ph9bWVmXHJxISEuDxeJCSkmJ1HOoGS4ze6IcffsDBgweV3LwHgquvsWPHIjs7m+MTEYwlRr/Q3t6Offv24fLly8oWmKZpWLx4MebOncvxiQjHEqO/UFdXB5/Ph7q6OiULzOFwICYmBi6Xi9eMsAmWGL1048YN7NixA36/X9nxiZSUFOTn5yMxMdHqOGQQS4wgpcRXX32Fb775RsnVFxAssJkzZ2LFihVwOp1Wx6FeYIkprrW1FcXFxbh3757SBbZhwwZMmTLF6ij0DlhiCnv06BF8Ph9aWlqUHJ9wOp0vxydSU1OtjkPviCWmqLNnz+LAgQNKD69mZGQgJycHsbGxVsehPmCJKaa9vR1lZWX46aeflC0wTdPwySef4KOPPuL4RBRgiSmkvr4eBQUFePbsmZL7Xy/GJ/Ly8jB69Gir41CIsMQUcfPmTRQXFys9PjF48GDk5+ejf//+VsehEGKJRTkpJb7++mt8/fXXSq6+gGCBTZ8+HatWreL4RBRiiUWx1tZWlJSU4M6dO0oX2Lp16zBt2jSro5BJWGJR6smTJ/B6vWhublZ2fCI+Ph4ejwdpaWlWxyETscSi0Pnz57F//35lP33UdR3p6enYsmULxycUwBKLIh0dHThw4AAuXLigbIFpmoYFCxZg/vz5HJ9QBEssSjQ0NKCgoABPnz5Vcv/L4XBA13Xk5uZizJgxVsehMGKJRYHbt2+jqKgIgUAAnZ2dVscJO03TMGjQILjdbiQlJVkdh8KMJWZjUkp88803+Oqrr5RcfQHB/a+pU6dizZo1HJ9QFEvMptra2lBSUoKqqiqlC2zNmjWYMWOG1VHIQiwxG6qurobX60VTU5Oy4xP9+vWDx+PBkCFDrI5DFmOJ2czFixexd+9eZT991HUdI0eOxNatWxEXF2d1HIoALDGb6OjowKFDh3Du3DllC0zTNHz88cdYuHAhxyfoJZaYDTx//hwFBQWoqalRcv9LCIGYmBhs3boVY8eOtToORRiWWISrqqpCUVER/H6/suMTycnJcLvdGDBggNVxKAKxxCKUlBLffvstjh8/ruTqCwjuf02ePBlr166FpvGlSt3jKyMC+f1+lJaW4tatW8oWmKZpWL16NWbOnGl1FIpwLLEIU1NTA6/Xi8bGRqXHJ9xuN4YOHWp1HLKBHktMCDEAQFHXfRsB5Eop/WYHU9GlS5ewe/duZT991HUdI0aMwNatW9GvXz+r45BNGFmJuQH8Xkr5hRDijwBWAthrbiy1dHZ24vDhw/jxxx+VLTBN0zBv3jwsWrSI4xPUKz2WmJTyD6/8MRXAE/PiqKexsRGFhYWorq5WssCEENB1HVu2bMH48eOtjkM2ZHhPTAgxD0CylPKUiXmUcvfuXRQWFqKtrU3Z8YmBAwfC7XZj4MCBVschmzJUYkKIQQD+DUBON7dtA7ANANLT00MaLlpJKXH69GkcPXpU2U8fdV3HpEmTsH79eo5PUJ8Y2diPAVAM4B+llFWv3y6l/AzAZwCQlZWl3rXAesnv92PXrl24ceOGsgWmaRpWrFiBzMxMq6NQFDDyJfBvAGQC+I0Q4jcA/iil3G5urOj09OnTl+MTKhaY0+lEXFwc8vPzMXz4cKvjUJQwsrH/RwB/DEOWqHblyhXs3LkT7e3tyl68dtiwYcjNzUV8fLzVcSiKcDPCZJ2dnfjiiy9QWVmp5KePQPDt45w5c7B48WI4HA6r41CUYYmZqKmpCYWFhXjy5ImSBfZifGLz5s2YMGGC1XEoSrHETHLv3j0UFBQoPT6RlJQEj8eD5ORkq+NQFGOJhZiUEt9//z2++OILJTfvgeD+18SJE7Fhwwboum51HIpyLLEQCgQC2L17N37++WdlC0zTNCxfvhyZmZn89iEKC5ZYiDx79gxerxfPnz9XssAcDsfL8YkRI0ZYHYcUwhILgatXr2Lnzp0IBALKjk8MHToUeXl5HJ+gsGOJ9UFnZyeOHj2K7777TsnVFxAssNmzZ2Pp0qUcnyBLsMTeUXNzM4qKivDo0SMlC+zF+ER2djbee+89q+OQwlhi7+D+/fsoKChAa2ursuMT/fv3h8fjwaBBg6yOQ4pjifWClBKVlZU4fPiwkqsvIPj2cfz48di0aRPHJygisMQMCgQC2Lt3L65evapsgWmahk8//RSzZ8/m+ARFDJaYAbW1tfD5fKivr1eywBwOB2JjY5Gfn4+RI0daHYfoL7DEevDzzz+jpKRE6fGJtLQ0uFwuJCQkWB2H6BdYYm8gpcSxY8dw6tQpJVdfQPDtY2ZmJpYtW8bxCYpYLLFutLS0oKioCA8fPlS2wF6MT0yaNMnqKERvxRJ7zcOHD+Hz+dDa2qrkxWs1TUNiYiI8Hg8GDx5sdRyiHrHEXvHDDz/g4MGDSq++xo4di+zsbMTExFgdh8gQlhiA9vZ27Nu3D5cvX1a2wDRNw5IlSzBnzhyOT5CtKF9idXV18Pl8qKurU7LAHA4HYmJi4HK5eMk9siWlS+z69evYsWOH0uMTqampcLlcSExMtDoO0TtRssSklCgvL8fJkyeVXH0BwQL74IMPsGLFCo5PkK0pV2ItLS0oLi7G/fv3lS6wDRs2YMqUKVZHIeozpUrs0aNH8Pl8aGlpUXJ8wul0vhyfSElJsToOUUgoU2Jnz55FWVmZ0quvMWPGICcnh+MTFFWivsTa29uxf/9+XLp0SdkC0zQNixYtwrx58zg+QVEnqkusvr4ePp8PtbW1ShbYi/GJvLw8jB492uo4RKaI2hK7efMmiouL4ff7lR2fGDx4MPLz89G/f3+r4xCZJupKTEqJiooKnDhxQsnVFxAssBkzZmDlypVwOp1WxyEyVVSVWGtrK3bs2IG7d+8qXWDr16/H1KlTrY5CFBZRU2KPHz+G1+tVdnxC0zTEx8fD7XYjLS3N6jhEYRMVJXb+/Hns378fgUDA6iiW0HUdo0ePxubNmxEbG2t1HKKwsnWJdXR04MCBA7hw4YKyBaZpGhYsWID58+dzfIKUZNsSa2hoQEFBAZ4+fark/pfD4YCu68jNzcWYMWOsjkNkGVuW2K1bt7B9+3YEAgFlL177YnwiKSnJ6jhElrJViUkpceLECVRUVCi5+gKC+1/Tpk3D6tWrOT5BBBuVWFtbG0pKSlBVVaV0ga1duxbTp0+3OgpRxLBFiT158gRerxfNzc1Kjk84nc6X4xNDhgyxOg5RRIn4Ert48SL27t2r7KePuq5j1KhR2LJlC+Li4qyOQxRxIrbEOjo6cOjQIZw7d07ZAtM0DfPnz8eCBQs4PkH0BhFZYs+fP0dBQQFqamqU3P8SQiAmJgZbt27F2LFjrY5DFNEirsSqqqpQVFQEv9+v7PhEcnIy3G43BgwYYHUcoohnqMSEEEMAlEgpF5gVREqJkydPory8XMnVFxDc/5oyZQrWrFkDTYu4ry9EEanHfylCiGQAnwNIMCtEW1sbSktLcfv2baULbPXq1Zg5c6bVUYhsxciX+w4AuQD2mBGguroaPp8PjY2Nyo5P9OvXD263G0OHDrU6DpHt9FhiUsoGAG/8dEwIsQ3ANgDvdAXpP/3pT/D7/b3+e9FA13WMGDECW7duRb9+/ayOQ2RLfd54kVJ+BuAzAMjKyur1z4FWtcA0TcO8efOwaNEijk8Q9QF3j8PsxfjEli1bMG7cOKvjENkeSyyMNE3DwIED4Xa7MXDgQKvjEEUFwyUmpVxkYo6op+s63n//faxbt47jE0QhxH9NYaBpGlatWoUPPvjA6ihEUYclZiKn04m4uDi43W4MGzbM6jhEUYklZhJd1zF8+HDk5uZyfILIRCwxE2iahrlz52Lx4sUcnyAyGUsshIQQ0HUdmzdvxoQJE6yOQ6QElliIaJqGAQMGwO12Izk52eo4RMpgiYWArut47733sH79eui6bnUcIqWwxPpI0zQsX74cmZmZ3P8isgBL7B05nU7ExsYiPz8fI0aMsDoOkbJYYu9A13UMHToUeXl5iI+PtzoOkdJYYr2kaRpmz56NpUuXwuFwWB2HSHksMYNejE9kZ2fjvffeszoOEXVhiRmgaRqSkpLgdrsxaNAgq+MQ0StYYj3QdR0TJkzAxo0bOT5BFIFYYm+haRqWLVuGrKwsjk8QRSiWWDccDsfL8YmRI0daHYeI3oIl9hpd15GWlgaXy4WEBNOuUkdEIcISe4Wu68jMzMSyZcs4PkFkEywxBMcnNE1DdnY2Jk2aZHUcIuoF5UtM0zQkJibC4/Fg8ODBVschol5SusR0Xce4ceOwadMmxMTEWB2HiN6BsiWmaRqWLFmCOXPmcHyCyMaUK7EX4xMulwujRo2yOg4R9ZFSJabrOlJTU+FyuZCYmGh1HCIKAWVKTNM0zJo1C8uXL+f4BFEUUaLEdF3Hxo0bMXnyZKujEFGIRXWJaZqGhIQEeDwepKSkWB2HiEwQtSWm6zrGjBmDnJwcjk8QRbGoLDFN07B48WLMnTuX4xNEUS6qSszhcCAmJgYulwvp6elWxyGiMIiaEtN1HSkpKXC5XOjfv7/VcYgoTKKixHRdx4wZM7By5Uo4nU6r4xBRGNm+xHRdx/r16zF16lSroxCRBWxbYpqmIT4+Hh6PB6mpqVbHISKL2LLEdF1HRkYGcnJyEBsba3UcIrKQ7UpM0zQsXLgQH3/8MccniMg+JeZwOKDrOvLy8pCRkWF1HCKKELYoMV3XMWjQIOTn5yMpKcnqOEQUQSK+xHRdx/Tp07Fq1SqOTxDRL0R0iem6jnXr1mHatGlWRyGiCBWRJeZ0Ol+OT6SlpVkdh4giWMSVmK7rSE9Px+bNmxEXF2d1HCKKcIZKTAjxHwDeB3BASvk708JoGubPn48FCxZwfIKIDOnx5zQLIbIBOKWUHwEYLoSYEPIQXRfvyM/Px8KFC1lgRGSYkZXYIgDFXb8/BmA+gJ9f3CiE2AZgG4B3/vE3KSkpcLvdHJ8gol4zUmIJAO53/b4BwPhXb5RSfgbgMwDIysqSvQ3gcrkwduxYaFrEbc8RkQ0YaY5GAP26fp8IA29Be2PixImhfDgiUoyRQqpE8C0kAMwAcNu0NEREvWRkJbYbwNdCiOEAVgGYa2oiIqJe6HElJqVsQHBz/xSAxVLKerNDEREZZWg3XUpZi//8hJKIKGKEdJOeiCjcWGJEZGssMSKyNZYYEdkaS4yIbI0lRkS2JqTs9bc7vvnBhKgGUNXLv5YCoCZkIXrPyuOrfO6qH1/lc3+X44+WUnZ7gdmQlti7EEKckVJmqXh8lc9d9eOrfO6hPj7fThKRrbHEiMjWIqHEPlP4+Cqfu+rHV/ncQ3p8y/fEiIj6IhJWYkRkEiHEICHEMiFEitVZzMISU4AQYogQ4uu33D5CCHFPCFHe9avbj7LtRggxQAhxUAjxhRBilxAippv7aEKIO6+ce0iv1GxliQghhgEoA/AhgOPdPa9mn384hK3EhBD/IYQ4KYT4H325j1nHD8OLuaci0YUQ+7sy/nUIj5sM4HMEr5XwJnMA/IuUclHXr+oQHr/HIum6nxnPvRvA76WUywA8ArCym/tMB1D4yrlfCNXBjZRI1/3Met1PAfAPUsp/AXAYwKxu7mPa+QMvX/c/vuX2Pp97WErMyGXfzLw0nMHHNvPFbKRI/juAM10Z1woh+ofo8B0AchG8yMubzAXw34QQ3woh/neIjvtCj0Vi1nMvpfyDlPKLrj+mAnjSzd3mAtgkhDghhPAJIUJ5xZoeS8TM172U8ksp5SkhxEIEi/Tbbu5m5vkDwL/iP6/R8RdCde7hWoktwi8v+/Yu9zHz+GY+mUaK5NWMJwGEZBBQStlg4KfxHgTwkZRyHoCJQojpoTh21/GNFMkimPfcQwgxD0CylPJUNzd/D+ATKeV8AHUAVofquAZLZBHMPXeB4GsvgODr8HWmnb8QYgmAJgS/eHVnEUJw7uEqsdcv+zbkHe9j5vHNfDEbKRIzz78nJ6WUz7t+fwVAyC+Q3EORmHbuQohBAP4NwJveop+XUj7s+n3Iz91AiZj6vMugv0PwC+Pabu5iyvl3bRv8E4Bfv+VuITn3cJWYkcu+mXlpOCOPbeqL2QBTL43Xg8NCiGFCiHgAKwBcDOWDGygSU8696x9SMYB/lFK+6Xt6/yyEmCGEcALYBOBcKI79goESMe15F0L8SgjxV11/HIjgF+fXmXX+vwbw71LK7o75QkjOPVz/UIxc9s3MS8MZeWxTX8wGhOXSeEKIJUKIv3/t//6fAI4jeDGY/yulvBrC4xkpErPO/W8AZAL4TdeHNf8shPjda/f5LYA/AzgL4Fsp5ZchOrbREjHzef8MwH8RQlQAcAK4F8bz/xTA3wkhygHMFEL8qZv7hObcpZSm/wKQhGAp/B7A5a7Av+vhPgPCfPypAM4DuIDgJ3Vm/Hco7/rfJQD+/rXbRgP4CcD/QfCtrTMcz00Ynvv/CqAWQHnXr38O53Nv8bknA/gCQAWAPyC40a/Eub92juUAJpt17mGb2O/6hG4ZgAopZbcbfUbuY+bxrSaC1/acD+CwVOzSeHZ4fszCc+/bufPbjojI1jixT0S2xhIjIltjiRGRrbHEiMjWWGJEZGv/H+ms7ZnaSUDZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "x = np.array(range(5))\n",
    "\n",
    "ax.fill_between(x, x, x+1, color='grey');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　接下来请你基于下面的代码，模仿出下图所示的“彩虹”：\n",
    "  \n",
    "<center>\n",
    "    <img src=\"imgs/rainbow.png\" width=400></img>\n",
    "</center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-03T10:51:37.339636Z",
     "iopub.status.busy": "2020-11-03T10:51:37.339636Z",
     "iopub.status.idle": "2020-11-03T10:51:37.343627Z",
     "shell.execute_reply": "2020-11-03T10:51:37.343627Z",
     "shell.execute_reply.started": "2020-11-03T10:51:37.339636Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TAYevX/E4lN5AV0/fBgA/ArAODhsipYCuqYzIj9+2Rbh0hZTCmBqvgGs6kjKIc2pkjAEZifERTYcOKIydLfuZi6KyGmJjwmDjBRJCauF5ZYeTIWD/6Gp9fLrJaYXO1wY/2H1Kv3Rq0rXORLDTuc/093b/o8PXr2gcSq+jq6fvTthbLZzajRQP0+IjN2+SldHS60dSGGxqmNRdrcNl9/8nrTVACskTmg71K6TnynvgUpESiG8kceGlQCRCQUztRtLVeCq1FgWjnPY1PXdolB58LinKqDOlYS8d/XR/b3fIhqtLh0PpVbp6+qIA/hLA3Shjuf+KrW3m1ss6ZOnzLdIRadTVsSTK3XdERmsYUjhxWNPhAwr5lbJVRgAdnRDbLiNUVJLwyjiTA9to7qmhtXo8Uy1djqqcGZ3DvQ8fRTavNdzqTBkAQwDu6O/tPujw9SsOh1JRV0/fZthm/utQRv3ofdevx4WdpdePpDCmqSKDa2JnZIXn3qP+5WnayaOaBvYp5Ffw+dCO9RBd7yBEomWFExFwdKqJDoytFi5F8LlMAV9/6IgZm866Hk8xsLWmXwPwD+f76hyHEoCunr6PAfgr2KMiJX9TlVs/UsIg0TxmEs1j0rWYTUQEowXODmrqf04hM+/2oOVGCGD9BSS27RCQSpez52kyW4ldg3HKaWVKvdxAa4Pvl1dnAuzq3L8B+L/7e7unHZ+x7J3XodTV09cA4Ksoo5l/efUjMhGp5bUdSayqcl+KJ983mJ8F7XlSYmrc+TnLmheBuOhSjfVbFKQ0Qrjt4i5oiaeGOsxYpsap80AAdaYs7CUF7+/v7X7S9SHL2XkbSl09fTfAXpVdD7dmbLZ+lGgzt+4svX4khTGNFVlcG0s6T9fIaA1fK9r/NCF54vy5EvfN1NZB7LxWo6FZCs9z+jshAo5MNpsXx9ukS8fcM6PzuO/hI8jkdTm9wDMAPg/gD/t7u8+rU9bnXSgV9x79OYBPwf3uNYp4Unzgerfe2VIYbG6cMF2rRpymay9P1ZIn7FTNX/jvWTJE5BtNhqSQQgpPwuQ1KKfJFDSRJoAAIQVERAoZVUJW2BkQ2UOtRkSkEMq9tUhJYusgdlwFeJ7zHqfxTBV+NhhHwShT6gUGc5kC7n3oiBmdzrruZwLsdO4M7KjpJcdnLDvnVSh19fRdAds7uxWOq2tSQNdWReTHb7vAod0IGU8YeWX7INpr3ZbmSfsa2aykZ58QmFy4uxFNcTWJDCE/NKczx6ZEbnBOFkbTKIxnoGfzb+v4m6xU8JoqEWmtRrStGpUbG3VlZ7306qKCfGNEVAnhXEl7C14E4pIrNDrWKeG53ZGX9RV2DXaa6XxFyUdUtCH88KlT5Xa1NAByAHoB/EV/b/cCnvsJh/MilLp6+qoB/AmAX0EZN9N6Sph1q+vwoRs3yopIab98BYyu9nx5/dpTwuUg7cujo6MHDR3cJ0HBNnEjQ4YKWpCBSB+a8Of7R7zMkSkUxhfm2ImsVKjc0IjqRLOp3d4Gr7FSgkjL6AIczm1pg7j8BkK0wunwryFg38hqfXKmSblM5/YdG6MHnjpdziUFgB01nYI9otLv+IxlYcWHUldP3y0AvgagAY6jI8DWj27oajfXda0puX6khKHV1XPmivZB5XKdEWmtkU1LevoxgenJkr/+DZ9bDCKT05h5Zohmnx+WueRMSQ0AgqLqo6i9uBX113ToirV1CiAtIwEGlFIQXZdrxDc6j5qSM3X03HCH07aBsxNp3PvQEUrnfGPI7f4/vDJq+jyAP1qpfZpWbCh19fStAfC/YVfWnMNIADoaUequmzdhw5q6kr9eCYNtLSNmS9OEW/3I94EThzS9uFcFNToyea1BpGafH9ZTPz2jcqfDdTZU1UZQ94411HhzJ3n1FUJ4koQM5lJKrFoNccWNgBdx2j4wnavAT890Uk57ptRd4Jmcj28+dkwPjs2Xc+ccYHeCT8FuHfi3Mp4TSisulLp6+iIAfh22TUQEQNT1WUoKs6qhEh+9ZbOsry71MWQ8aeS1sSRaHXZnk9Ea+bwdHU2Mlvz1/+55RER5A38qS+M/PiHn9g6DCuHv413RWY/m29bpmq5WBSG09AK4lNKLQFx2rUZbzGmFrqAlnkzF9Xi2SpRaZyIiPL5/yOw6cLacNijnpAE8DuBX+3u7T5X7sLBYMaFUvJH2dthNkC1w3Hd0jqcEdmxepd99eVyVegBNwOjaSEFcv/aUdGk1Qr5PGBk09PyTZa+skSFDvpGZ41N6/IfHVPb48tyTp2ojaLy50zTd1CmhRDBTu7XrSey4WkAqI2Sp4QIcGGs1R6ZapMvi2omzs/jmo8eQK5S1bQCwl2L6AO4B8Cf9vd3L9HDjK1ZEKHX19F0G4IsAulBmGAEwEU/K91+3AYnOxpK/WAlD7TWz5vI1KVXq9UbFtiKC9j5FOFPevqNzYZQ+OK7HvndU5YdXxg5vEZVovD5OzbdvECIiyw+n6lqIq242qK2DUKUfVUnN1eLpobVwqTPNpgv450eOmtHpDMqczgF21JQH8P8B+NvlvLdpWYdSV0/fNgCfBXAT7AbIsn6QlRSmua4CH71ls2ysLbm5JKQw6Fo1TJsdeh+R1hrpOUm7HxGYny35s19+DhFRwYj0kUk9+p1DqjC8Mg+fi4hE402dpuX2DRKeLG9aJwTExZdpbLhACVV6EXwmH8VPz6yjrF/68RRjCI+8MGiePjgSxHQOsFeJz8HeQXhff2+3+0HKJbIsQ6mrp28H7L6Nm2FrRmUP5T0lsHPzKv0uh+maPS5i5DWu9SPfJ5w5YWjf0wrGvc5jcppyZ+do5BsDMmzF64UiKz00d28wjTfEpfCkKasg3haDuOIGQHklT+dsnWmtHs9Wl1xnAux07luPHUMu79zV8rXmAMwA6AFwb39vd/lNuRbJsgml4i0i74K9iXY77Mio7BUZAeiKiFIfvHEjNsXqHb7evX708nTt+V1A6nTJn32OyWttMr4c/ueDYr6//KL4cuQ1VaLtw1t1daJFyWgZP9OVVRBX32JQV1/ydK5YZ9JHplqcmsfNZwv49uPH9eDYfDmbLV9rDnZa9xcAvtLf2x3cnpIFEvpQ6urpWwXgEwD+E4C64j+B8JSgjlU15kM3bFQ1VZGSv76s+pHWGpm0pCcfcp6ukTaGNMmJB0+YyYdOSvLD/d9yMVRuasSaT2wjr76CZFS5/dISAqLrHRrrtjjtaSqnzkREeHpghB7eM1juZsvXSsP+Ev8X2KL482FtkRLKUCqeT7sddgf2zQA0ythr9DpMREl522UdznevSWFwiWPvbPJ9wtkzhvbsUtBuU36T15Q9MWXOfu0l5U8u2h46H/abm2C3W1QW/10edhUIsN/4UdgbX3zYzX6m+O+cd9OXRAo03txpVt2xSQpPlDwVe1l7HOId1wHKo1K/SWbzUTzhWGcCgNGpDL7x6DGans9TGWfnXo+G7UQwCtt//hthu5MuNKHU1dPXDDs9+0UAt8F+Qwc2KjrHU7aYfddNm2RzvUtzAFs/urbjtFO7EfJ9UP+zhJNH3E6w+0abvFbDX38Rc/sWdKpWgA2gGgCDAPYCeBbAEdjjDoMARhOp5OvWKgZicQmgEcAaAJ0ANsGujl4BIAEbVASgdqH+AF5jBdbcfbGuXN8gZVS5jThq6iCuvZVQWV3yEZWCkXgqtVaPZtzqTNoQHtk7aJ4ZGJEBj5rOyRSfeRz21MMDAF5c6hHUkoRScU9RDPYb9EYA3QDWw/5WDTyIishTQtxwSbu5dtsa6XLVkYTRddG8uG7taVnllVg/MsagkJf05MNw7Xlk8hpz+0b0yDcHlMkEfi6TAMzCjn76YbtwPgbguUQqGegSXjGwtgC4DsB7ANwKO8KqgB2BBaruHWuo7SMXChmVWiiHVTrlQbzjOqfNlvSqCzFdV/1TY/P41uPHaS5TMI6dLd+OHOxAoAD73/3HAJ6GDalF3V4QeCh19fQ1wg7TK2EDpgX2t+VaABcBuAT2GzICO+yvRQAF6zfjKWFa6ivxoRs3yhan0ZGtH8Xrps3O1UMlL86R9g2mJ0G7H5Eu7WnJN9pkfTX0DweQPhh4E7dZ2NWePgD3Afi3RCq5qBvwiiG1A8D7AXwMwCrY74/AAkrVRrDm7ot11eYm91HT5ouMuOhS6bJtYHi+BruH1sI3suQ2KIC9QeXRF1ILOWp6rTTsVK8SQBLAiwD2ATgJ21N8FLYZ3bn9UeNBbT8INJS6evraAAzDDgsN7B+KYEOnEgvwW/DNCMB4npS37XSvHZ27e23n6hStq58p+QHk+4RTRwz1P6fg8Hdt8prmXxwzw/e+FOToKAP73+RnsHWFHyVSydAc7hyIxbsA/AcAn4QNzMBGz3WXr6HVv3ihEBHpVmtqWQ1x9c1O2wbSBQ8/PbPOzBci5HLnHACMTGbwLz89biZnc0FsuCwVwYbQuW9EBft9VA3bjK43iA8JOpQ6AbyE8ndVl81TApva6/UdV69TtQ4ra4Bd7q/0tLyu47RoqChthGOX+7WgPbsIg6dKDzNjDOWNPPv1FzG3d6TUL38js7DD83sAfCWRSob68reBWDwC4A7YjYDbYX+puR3xfxWvsQLtn95uKtpr4bRCV1kNce2tBjV1EKq0r9dGYM9Iuz4zW+90ewpgV+ieOzRKD+0ZFL42uoyuA0H6s/7e7t8P4kErLpQ8JUxNZUTcee16sd7hVP85ShhqrZ43V7YPqogsbUMjGaORz0na9ROBmamSP9vktcml5jD0lX3Snw7kNpI52A6GfwTgO4lUctk1ChuIxS+CPULxAdipS+lb7l9NAM3vWm+ab98oRUSWvLoGKSF2XqPR3ul0qPfUdD3tGYk5tUE5Zz5bwIPPJvXB01NqkaZ0b4ZD6bWkFNpTQr3z0g66fGurcClkW0SyeFW223ER32BqwtaPCqVvojV5jYkHT5iJB0/IAPoazQM4BOB3ATycSCXDsdRahoFYPAYbTv8BrxTHnVXE69DxqztI1kSM01GVjVtJbLtMuOxnmslF8bPBTsr4ntO2gXOGxtP4/u6TZnw6JwraLFUwcSidIwS0kkJdvrXV3HBJTFaWsZtXwOio0vK6jqRoqiy9xEK+Tzh52FD/86rUTmmkjdZpX6b+6gWRPVn2Sf45ACcA/GYilXy03IeF0UAsvhp25Hc37JTOuV4pKhTW3L1N11y4yq0I3twKcfU7AS9Scp3JNwLPnY3pofk65+kcYKd0h89M40dPn6ZMzqfC4tebOJTOhVHXhmb9zh0dznWjc5Qw1FY9Z65Yk1IRVeJ0rcz6kclryhybNENf7S+3mD0PYAL2UsMfrISR0VsZiMXXAfgcgPeizEPZ9VfHqO3DCeE0nausgrj2Nqc6EwCcmm6gPSPtZU3nAHvAt//EBH7y/BnKFTQtYjE8sFAqu2i42KQUWgqo7ZtacOMl7airLuegE3Bude3S1iGsb5hWJU/XjNHIZyXtegiYmXIJJIz94BhNPXKqnD9HFraA/fsA/no51oxcJVLJUwA+NBCL7wTwNwC2wvGX4szulMiemkHHZ3ZA1UVL6zyQzYAefUCKnddoau+kUutM6xqmRUtVGrsGO2nej5DLZksAkFJg+6YWdG1oFv0nJsQjewcpk9NU0GaxR07Ols1IKaKEkVLKKy9sM1cm2mR1Zfl5KoUxNV4B13QkZV209PpPOfUj0kbrjK9SX34BZUzXCDaQ7gXwu4lUcsL1QSvBQCwuANwF2wa5Co7HWkSFQvsnL9bViRa36dyGrSS6LhMu+5kMAftHV+vj001Oh3pf69y07rF9KT02nVW+pnKbyr2R82OkdG6K1lJfaa67eI28sLMRKqB7w4p3r+HiVSNONfFi72yiA3tKrh+ZvDa5M7MY/KsXYOadN8ueu93i44lUco/rQ1aS4nT1GwOx+A8B/A8AvwSHKR3lNFJ/vU813hQ3q35hiyi568CJQ4KmJwCHOpMUwKVtw6qjdha7h9aioKUupwguhMDWeCO2xhvV8GQGu18cphdPTQCA9vWC7Q4vS+hGSgIwnpIiGpG4dHML7dy8yvGM2uuTxWL21bEzosXl7FqZ7UZMXmPqsdNm7PtHXVfXzh2A/QMAX0ikksuuiddiGYjFd8DuUo/D8XuyckMDOn51B2Slp4Uq7aIAVFTZ/Uy1dSSUV3IAFLTE88PtZRfBXytf0Dh4egrPHhrRZycySgDaL//4ysoqdHtKaCKo2qqI2ba+CRevb5ZrmqvgtgP7jSlh0Fk/pbe3DrtddWSMRi4jaddDArOlTbnIEFFBi6G/68f8AedLJOcB7AHwsUQq6d6A6TwyEIt7AH4btg9XBRymLqo2go7P7DDRWC1kpMQitpAQl16psXaD8zXiqblaPHu2A76RutQbVN5KOutjIDmFfcfG9eDYvFJSmLxvgNL/npZtKJGSQisppK+NrK2K0LrVdXpzR723YU096qoX5hSKhNFRT8ur2s8Il5P9AEC+bzA+TPTMEyU38ze+0f5UVg5+cY8ojDp9/rkWIL8J4O/Oh1W1oA3E4lsBfBvARriMmqRA6wcv0A1Xd7jVmeIbSVx6lYBSpa/sAchriT121OR0Iebb4WuD5Og8jqdm6Ghq2oxNZ5WAAAR0wTcCbx5U4QylT9+354LdLw0fAuwkXimBqKeoqkJRQ03UtDVVybaGKtnaWIW2xkpES7xltnR2I+TmxgmzrWVUltqI7eWnaB80sN/g8IGSvxtMXlN6YNwM/X2/orxTq9t52FP7d/HoqDwDsbgC8HuwU1+n7QO1O1fTmo9tEyLqsG2gvgni2lvsTb3S7cKD4fkaPHM2RgWtjOv5ubeLiDAxm8PIZAaj01kankybydk85rIFmSto4fsGpvgjddG6ph9881NX/XwQnxtoKP3L4ZFObcyAgKhy31EdDCUM1UZzdOWaQVlf4daemMhoFAqKnnoMGB8u+etNXmP8h8fM5EOnXH61EezB2T8E8JeJVDL8l7QtEwOx+HYA9wNog0PzwGisFmt/bSep2ogpuRVKJAJxxU0aza1CeKXfngLY83Mvjreao1PN0pBw6joQFCKCNgQlxZ9/aOvq3wvimYH/YZSUZikDScLoiNTY2TaEWztPuAeSbTci6KHvlxxIZMjojI/BL++FYyBlYFtEXJVIJf8nB1KwEqnkPtg2Ol+HPfVeknxqDif/+EmROTEtTF6X9t+mUADt+omiQ/tB2m07mZKES1pH5G3rjqOlMkNKmCWbzgsh4CkJIURg77BsNlS9NTJSGGxqnBDv2XgE6xqmnevk5PvA8UNEj/1IIldaDcj4RhfG0uLU/9iNzGGnHu1p2H1H2xKpZL/LA9hbS6SSmUQq+SsAPgzbF6ikQqHJ+Djzl8/JqSeSZPIOC6CHD0ja9RAon7MNAB3URfO4KX5SXdV+RlSqAklRxlU4IRL49A2LfiCXjBQk22vm9PbWs8rlRtpXnmQMtC/p2SeA4VTJX2/ymuYPjpmzf39AOVyJ7cOOkD6eSCW/V/KHM2fFQ77fBXAxHL53ay9tw5pPXAynOlO0wl6G2dAM1+kcYDddHp9qogPjbcKQ0IYWtt70Ov7sgxe0BVLoXsYjJSIpDNqq5umWzhO4OnamvEDyi90hH/qeayBh7IfHaOgr+10CKQ0b5hdzIC2+RCqZAnAtgP8F+4uhJHMvjOD0Z5+GnsmDtClt2JTPgZ74saTD/c7TOcBuutzcNCnu2HgYieYxoYSGFCW+S0gsw5GSHRm1VqV116ph1VhZfr8h8n3Q0Rc1Du4v/XS/IWNyWqa+8kI507WvAvhPiVRy2V61vFIMxOLvBPAd2O/hkvaoyCoPsf94qansrHdrHte0CuKqm4urc+WNdApa4shUszk82SIXaeQU2Ehp2YSShNEQUGtrZ/SFLWPK5azaa5HRGvm8pKcfE5go/WYQU9Dan8zKM1/YI/yJkludaNjfyh/j0VG4DMTi7bAXJ1yEUlfnBLDqzi268Ya426WYXgTisms02jqcN1u+mm8ETk430sDEKhSMQpA7w18jsFAK9dm34gl+eFJjS9OE3NgwiagygSR+8e410N7dotTNkMDLvbNx9h8PCIfpWga2E2R3IpU8VvKHswWVSCWHBmLxq2Fvlf0VlBJMBIz96xGVPT6FNXd3lV5n8gugpx9X6FhP2Hk1IJX7vXUAPEnY3DQpNjVO4ux8LQ5NtuiJbJUiQlln6hZSCEdKVFziFLK9ZlZvapxUq6rSZXSYec3TjdHQvqI9TzpflW3yGmPfP2qmHj3t8s0yD/tb+JcSqaTb9nK2aAZi8Tth70SrRok12OjqGnT8+k7y6qJGuHS1rKyGuOJGjYYm5z1NrydT8HBiptGcmG4Sea2EJqFR/vGVlTV9EyAthZECEKtr5vS6+mm1unoerjuw3wj5PmF82NBzuxTyDp0ljTEmq2Xqr15A5tiUyytkAPy/iVTyr12+mC2NgVh8C4AHAbTD7gR/22Slh/ZPXWKqNja61ZkA2wrl4p2i3FHT65nOVSA5W2+SMw3IaE8KQGu3+tNyDiUiJYw5l8wNFVkdq5mVbTXzoqkiG9iI6P/4xHOjo727gcFTTs8wBa3zw2kx+KW9UpfezL8AYAbAexKp5DNOL8CW1EAsXgPbceAWlDoTEEDz7RtM87s2SKc6EwBU10C84waNhqZAak2vJ+N7GEnXYGiuVo9lqmVOe0IJYzQJehtTvXCG0rNnD19waqbxkBIGBIDI/t150qBS+aYmmjdNFRnVUJETjRVZ1EQKCxJCr0a+D5w9o2nf08rlIkjA1o9mnhkyI98aUNAl/32lARwA8HOJVDKwu5LY4is2kfvPsL3BS24gV51oRvsvb4escLxzDgA6N5G45AoBpXS5K3RvJa8lpnKVmM5VYipbqWfyFcj4nswbJQwJSEEQADRJtFXP3X/D2o3vC+JzA74h97HOdME7ThBKCQNPGihBCx48r4e0b685em6XwJjb9WZERJQ3YvjeF2n2+WGXP0UawN8D+K3zqUXtSlfcNvBd2BFTSYtFXlMlOj6zw0Raq0hG3A7lIloBsf1KjTVrlcstKkEwBLuaZwQMCVR4+nMRecN/DuLZgYcSlvjeNzLGwBhJh/sNDr8oQW47741vtJ7JycEv7hX54fmSXwO2fvTpRCp5r9MLsFAbiMU7YetM61DqqEkJtN2V0PWXt7tfIQ4ALW0QO68lVFZRkIVwR38G3HS+7+j+PxERkfaBoSTRT/4VONTvHkh5TfMHRnHyj590CaQ87D3r13EgrVzFNjI7AfwAdkX17dOEkfsOqrNfexEmp0HGcWQwPgL6yf2C+p8VVMiDtF6WO7hfa0WEEvk+YWqc6Ikfg555XCHr2MiNiExeY+TbAxj6m/0u/Y/SsJ0htyVSyb1OL8GWjeKWjo8A6IHL8ZQ9w+LUnz6FwlgGpuAaKAScPCLox98Bjg8I0r5d2FnGlvX0jXyfkJkn2v+MxMhQWc8yvtZ6Ji8Hv7RX5IdKHh0BNpD+DnbJn+tH55mBWPwm2B5NJdeZhCfR+uGt5U/nAHv/3EU7NNauVxBlFNRLF9j0bdmFUvHiRyA9R3TgeYnhwbKfafKa5l4YNsP3HXQ5THuufvSpRCp5X9kvw5atsupMAGouacWauy+GjAYQJlU1EBdu11i7QUFAu3a6LMH5F0pkjAEZiclxTQdfUBgrvRPkv3umNoYKRp79pxcxt89ptT4PYArA7TxdYwAwEItXwa643gGHnwOvsQKxT2830fZa982Wr1ZRCbFlm8GGCySE0C63qrxN508oke9rAArJ45qOvqgwNxvIc01em9zgLIb+Zr/0S98MCdjp2gsAfiGRSjpfT8JWnuJ+pt8A8KdwuRBTAE23rjct79kona4Qfz3KA+IbSFxwMaGiSkBKCnhqt7JDqbiKoDA9oenYgELqNBBQ7Y4MEflGjH3/KE09dlo43r2WBvAVAL/N966xNzIQi18Pe86xFg6H36OxWsQ+vZ28xgrjvKfp9TS2QGy4wNadAAPliQCCb2WFUvGCRwMhFWamNJ06qpA6BeRKP5/2Zkxem8JoGqm/3S8LIyW3ZgZeqR/dnUgl/yXQl2Mr0kAs3gGgD8AmOFxSACWw6uc2m8Yb48GNms4RAmhrh4hv0lizVkGAiufrnM6+LetQIqM1tBFQUiKbIYwMGTp7RmH0LFzaiLwVMmTIN3L8h8fM5MOnXG+mzQIYA/DuRCr5UqAvyFa0gVg8CuDLsNsHSg8mABXxOrT/8iXk1VdQILWm19PYArTFSLTHDRoaFYgIQmhIpd5GGIYzlOjsvVvEmo7DVCguYQkICCkgJVDIA5m0xswUaHJMYXoCmJpYkBB6NZPXlEvN0dm/75eFMedOIfMAngDwkUQqORPc27HzyUAsfjeAL8HWmUof8UhhD/betl4KTxohF/JqJQHUNQCNzRCNzQaNLYSaOolohYAQtpxCMAAgIhFJ4yPfFi0f/nAgnxxkKJnvfaoTDU2nICWgtQ2cfB4ubULKRb7RpqDVyLcO0ewzQ+UMeTMA/huAv+CbaVm5infO9QFoQoltUM6JtFZjzd3bTEWsTsiKMvc1ufA8IFoJRCK2gC4kkJm7R777C78VyOODeMjLjAYmx+axlGffiIgKRsw+dxaj3z0Mk/Fd/6MVAMwCeF8ilXwiwFdk57FEKrlvIBa/EMA3AFwPh5+Vwmgayc89K2t3rsbqj1wIEZU60EL4W/F9wJ977b8NrGHhijhmco7JacqenqHTn30Gw/e+pEzGeWP1PIDnAFzEgcSClkglpwG8B3YE7vzDPLdnGMf/8KeYeiwpTF6DjONhz5AJeY/ut8fktdFzBTHyzYNi/sBYucPZDIB7APwXXu5nC6VYCvjsQCz+U9htA/UAKkp9DuU0xu4/IqceT6L1AxdQzbZVEJ4kIZeiYVAwlnUombzWJqfV2PeOiJmnhwTKu704D2AOwAcTqeSjwbwhY28ukUo+NRCLJwD8M+zdc06lD38yi6G/3a+isVq0fWirqVzfoALfQrBIlmUomZw2Jq/F+ANH5fTuFKCp3L/4eQDPAvhwIpUs/a4lxsqQSCUnBmLx2wH8GoA/g+vqHIB8ag5n7nleVXTWo/V9W2w4LfhKXbCWTSjZLpAa/mwe4w8ck7PPD6PMkRHwymbIHgD38OoaWyrF770vDMTij8FO59rguKcJAHKnZ3DmnudVNFaLlvdutNM6KbRQ4bxW6dVCH0rGNxpEKnN0ykw8eEJljjjdQvt60gCGYFfX+oN6KGPlSKSS/QOx+EUA/ieAT6CMYALsyGnob/Yr1VCBxhvjovH6tRBKGFmx5J0q31AoQ4kMGSoYodMFTP30jJzZPQg9kw8y4c+dXfu9RCpZ/r3fjAWo2DzuVwdi8e/Abh2ohUMR/NX0dA7j3z8qxx84hpqLV8mmmzt15YZGBSIto4u4neBtCE0omYIdEZl0gWaeO4vZZ8+K3JlgOgK8SgbAJIC7Eqnkz4J+OGNBSqSSDw3E4psB/DVsK5SyRk0AAEOY3z+K+f2jStZEULe9TdVfE9OV8XpF2mgRVXKpi+NLEkrFDY4aZD8/e2paz70wouZfGkdhNC3gWOR7CxnYzpC/k0glnU7jMrbYEqnkFIC7BmLx9wL4J9hgctoJ/lpmvoDpJwcx/eSgEhUK1VubVW1Xq66+sEV6dVFBvtEiooRQi1skDzSUsienKyrXN9SYvPZBBNhroQSkkMKT0PMFKoxlTPbUtMienPayp2dQGEkDhIUcPs4DGAHw0UQq+dQCfg5jCyaRSv5wIBbfCLuH7kMIYtT0KpTTL4+gAEBWe6hc36Aq4/VUubHRr1hTI1VDVAohQL4hAkgABCFIRKWXOzPbGdQLBXr27fCmDeuqE80nhZQgX8NkNXS6AH8mDz2Tg+PpfFc+7N6jP4U9t5Zf1E9nbIEMxOLXAvga7Ardoh7pklUevPoKqNoIZJUHEVUQSiB/dv7LG55+6TNBfEagIyWT8Wlu78iSnn0rmgewG7Zv9sklfhfGApVIJXcNxOJbAfwW7G29HoDoYny2yfjIZ3zg33ejng7qM0K7LOhoHsBpAB9IpJK3cSCxlSqRShYSqeRnAWyGvUUlg8WeiyyQlRJKGQAzAH4XwKZEKvngEr8PY4sikUoOJVLJu2A7DjyLUi/GDKHlHkpZ2P8InwOwNpFK/m++c42djxKp5PMArgLwQQCHYc9xLkuh2adUojTsUPULAD6bSCUnlvh9GFtyxaMqPy4e8P0FAH8BoB128+WysdxCaQ52Ve1zAL5Y7EvDGHuVYjjdPxCLfw/AuwH8dwDbYHeFh2r39utZDqF0bmn/FOzy/rf4aAhjb+3cyAl29LQDwO8AuBOAxtKvkL+hsIYSwbaiVbB9Zr7EN9Ay5q748/OLA7F4E4CPw7ZJ6cAibid4u8IUShq2aO3Bpvs/AHiQNz0yFpxEKjkJ4PMAPl/sRvBR2JBqLf5fSr/RN2BLGUoF2IJ1NYCTAH5Q/GdXIpVc2HuXGGMo3l/YA6BnIBbfBKAbwAcAXAk7SBBYgmneQoRSDWzgaNh60Lk+11EAEQApAP0AdsHuq3iG71JjbGklUsljAL4I4IsDsbgCcBFsOF0N4HIAG2APAp9b+Zaw5RUP9uc6sI2bgZ59G4jFPQC/DvuiWdi60ASAswDOADibSCVXxI0LjJ1vBmLxegCdsNsMVgFohJ3pRAA8kEglDwTxOQFf280YY+VZ7ju6GWMrDIcSYyxUOJQYY6HCocQYCxUOJcZYqHAoMcZChUOJMRYqHEqMsVDhUGKMhQqHEmMsVDiUGGOhwqHEGAsVDiXGWKhwKDHGQoVDiTEWKhxKjLFQ4VBijIUKhxJjLFQ4lBhjocKhxBgLFQ4lxliocCgxxkKFQ4kxFiocSoyxUOFQYoyFCocSYyxUOJQYY6HCocQYCxUOJcZYqHAoMcZChUOJMRYqHEqMsVDhUGKMhQqHEmMsVDiUGGOhwqHEGAsVDiXGWKhwKDHGQoVDiTEWKhxKjLFQ4VBijIUKhxJjLFQ4lBhjocKhxBgLFQ4lxliocCgxxkKFQ4kxFiocSoyxUOFQYoyFCocSYyxUOJQYY6HCocQYCxUOJcZYqHAoMcZChUOJMRYqHEqMsVDhUGKMhQqHEmMsVDiUGGOhwqHEGAsVDiXGWKhwKDHGQoVDiTEWKhxKjLFQ4VBijIUKhxJjLFQ4lBhjocKhxBgLFQ4lxliocCgxxkKFQ4kxFiocSoyxUOFQYoyFCocSYyxUOJQYY6HCocQYCxUOJcZYqHAoMcZC5f8HE6OF08nJWAsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#### import numpy as np\n",
    "\n",
    "x = np.linspace(-np.pi, np.pi, 1000)\n",
    "y = 0.8*np.cos(x)\n",
    "\n",
    "# 色彩列表\n",
    "colors = ['#D7191C', '#FDAE61', '#FFFFBF', '#ABD9E9', '#2C7BB6']\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "'''补充你的代码'''\n",
    "color=['#D7191C','#FDAE61','#FFFFBF','#ABD9E9','#2C7BB6']\n",
    "loc=np.linspace(0,1.5,6)\n",
    "for i in range(0,5):\n",
    "    ax.fill_between(x,y+loc[i],y+loc[i+1],color=color[i])\n",
    "\n",
    "\n",
    "ax.axis('equal')\n",
    "ax.axis('off')\n",
    "\n",
    "fig.savefig('rainbow.png', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 请在今天对应的帖子下回复补充过注释的代码截图"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
